Determinants of hamstring fascicle length in professional rugby league athletes

Journal Pre-proof Determinants of hamstring fascicle length in professional rugby league athletes Timothy M. McGrath, Billy T. Hulin, Nathan Pickworth, Alex Clarke, Ryan Timmins

PII:

S1440-2440(19)30545-6

DOI:

https://doi.org/10.1016/j.jsams.2019.12.006

Reference:

JSAMS 2215

To appear in:

Journal of Science and Medicine in Sport

Received Date:

15 May 2019

Revised Date:

7 October 2019

Accepted Date:

5 December 2019

Please cite this article as: McGrath TM, Hulin BT, Pickworth N, Clarke A, Timmins R, Determinants of hamstring fascicle length in professional rugby league athletes, Journal of Science and Medicine in Sport (2019), doi: https://doi.org/10.1016/j.jsams.2019.12.006

This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier.

Determinants of hamstring fascicle length in professional rugby league athletes Running Title: Fascicle length determinants Timothy M. McGrath1,2,3, Billy T. Hulin1,4, Nathan Pickworth1, Alex Clarke1, Ryan Timmins5,

2. 3. 4.

5.

St George Illawarra Dragons Rugby League Club, Wollongong, Australia Pitch Ready, Canberra, Australia Elite Rehab & Sports Physiotherapy, Canberra, Australia Centre for Human and Applied Physiology, School of Medicine, University of Wollongong, Wollongong, New South Wales, Australia School of Behavioural and Health Sciences, Australian Catholic University, Melbourne, Australia

ro of

1.

Corresponding author: Ryan G. Timmins

-p

ORCID - https://orcid.org/0000-0003-4964-1848

School of Exercise Science, Australian Catholic University, 115 Victoria Parade, Fitzroy,

lP

re

3065, Melbourne, Victoria, Australia, [email protected]

Abstract:

na

Objectives: Investigate the determinants of hamstring fascicle length within professional rugby league players.

ur

Design: Retrospective cohort study

Method: Thirty-three athletes underwent a testing during the early and late pre-season

Jo

periods. Fascicle length measurements of biceps femoris, 3D kinematics and elapsed timeperiods at thigh angular velocities between 20deg/s to peak velocity during a single-leg eccentric hamstring strength test, GPS-derived running loads, age and previous injury history were all recorded. Fixed effect determinants for fascicle length were analyzed using multiple linear regression. Results: Significant determinants of hamstring fascicle length were observed. Multivariate

1

regression analysis showed modifiable factors including chronic running volumes >80% of measured peak speed collectively explained 43% of the variability in the fascicle length data, whilst peak eccentric strength-related and elapsed time under load from 20deg/s to peak thigh angular velocity collectively contributed an additional 44%. Chronic running volumes above 90% of individually measured peak speed and the ‘break angle’ during a Nordic eccentric contraction were not significant contributors to the final model. Non-modifiable risk factors (age and previous injury) contributed the remaining 13%.

ro of

Conclusions: Managing high speed running exposure as well as eccentric strength training allows for ~90% of the controllable determinants in fascicle length within elite athlete

populations. An important contributor to the explained variability within fascicle length

-p

(superseded only by chronic speed exposure and peak eccentric strength) was an athletes

ability to achieve a prolonged contraction at long lengths during eccentric strength training

lP

re

rather than the angle of failure during the contraction in itself.

Keywords: Hamstring, Fascicle, Injury, Speed, Strength, Prevention, Sport

na

Practical Implications  Using multiple linear regression analysis with factors that are readily available in elite sporting settings, it was possible to determine ~90% of the variability in biceps

These factors included chronic running exposure >80% of a relative maximum

Jo



ur

femoris long head fascicle length, in elite rugby league players.

velocity, peak eccentric strength (during the Nordic) and time under load at longer leg lengths in the Nordic. Non-modifiable factors (age and previous history) also contributed to the explained variability in fascicle length. Chronic running exposure > 90% of relative maximal velocity and the ‘break angle’ during a Nordic effort were not statistically significant contributors.

2



These findings give practitioners the option to monitor alternative variables (instead of fascicle length itself) and be able to approximate (around 90%) of the impact it may have on fascicle adaptations in elite athletes.

Introduction Hamstring strain injuries (HSI) are the most common non-contact lower limb injuries in team sports that involve sprinting, kicking, jumping or high-speed movements1. Increases

ro of

in overall injury rates negatively influence team2 and individual performances3, which have

negative financial consequences for sporting organizations and athletes1. As such, identifying

-p

factors associated with HSI have important applications to practitioners in team sport.

A number of non-modifiable risk factors for HSI have been identified previously,

re

most prominently, increasing age and previous injury4,5. However, in recent times, a greater emphasis has been placed on modifiable risk factors and appropriate interventions, which

lP

may lead to reductions in an athlete’s risk of HSI 6. Of these modifiable risk factors, eccentric hamstring strength has received significant attention 7-10, with low levels of eccentric

na

hamstring strength reported to increase the risk of future hamstring injury in athletes from different football codes11,12. Recently, it has been reported that elite footballers with biceps

ur

femoris long head (BFlh) muscle fascicles shorter than 10.56cm (determined using a receiver

Jo

operating characteristic curve) were approximately 4 times more likely to suffer a hamstring injury in the subsequent season than athletes with longer fascicles13.. These data suggest that interventions aimed at increasing BFlh fascicle lengths and eccentric knee flexor strength should be prioritized in hamstring injury prevention programs14. Furthermore, it has been reported that the ‘break-point’ angle (i.e. the point that a steady state lowering during a Nordic eccentric exercise cannot be sufficiently controlled) achieved during Nordic

3

hamstring lowers was: 1) positively correlated to eccentric hamstring strength7 and 2) able to be used as a field-based assessment of eccentric hamstring strength7,15. However, the applicability of this measure to elite sport is still unknown. The risk of future HSI has also been related with spikes in high-speed (>24km/hr.) running volumes, which are relative to each athlete’s regular performance16,17. However, both over- and under-exposure to maximum speed (>85% of maximum velocity) efforts and volume (i.e. distance covered) is associated with the greatest risk of non-contact lower limb

ro of

injury in professional Australian footballers18,19. Although there is an association between running exposure and the risk of HSI, the independent use of running variables to predict future HSI may have limited clinical value, where multiple factors (including eccentric

-p

strength and fascicle length) may be needed to determine the probability of a future HSI 20.

re

As such, the purpose of this study was to evaluate the influence of elite physical training aspects on fascicle length changes in professional rugby league players, including the

lP

influence of peak hamstring eccentric strength training and quality of such a movement (i.e. ‘break angle’), as well as running speed exposure, age, and injury history across a single-

ur

na

season in professional rugby league players.

Jo

Methods The study received ethical approval from the Human Research Ethics Committee (approval number 2018-135H). Thirty-three elite rugby league players (mean age: 23.9±3.9 years, mean body mass: 98.6±9.6kg, mean height: 187±4.6cm) underwent a comprehensive performance battery on three separate occasions, separated by a minimum of 56 days (i.e. 8 weeks); December 2017 (early pre-season), February 2018 (late pre-season) and May 2018 (in-season). The following was tested on each occasion: 1) peak force output during a single-

4

leg Nordic hamstring exercise using a Nordbord (Vald Performance, Albion QLD AUSTRALIA); 2) motion analysis during a single-leg Nordic hamstring exercise using an 8camera 3D motion capture system (Vicon, Oxford UK); and 3) measurement of BFlh fascicle length. In addition, GPS-derived distance covered above 80% and 90% of each athlete’s individual peak speed over the preceding 28 (28-day chronic load) and 56 (56-day chronic load) days prior to each test was recorded via wearable GPS technology, which has demonstrated accuracy and reliability for measuring instantaneous velocity (Catapult Sports,

ro of

Melbourne VIC AUSTRALIA) 21. Anthropometric data and previous injury history were also recorded by qualified physiotherapists.

-p

An experienced exercise physiologist performed all motion analysis and hamstring

strength testing, whilst fascicle length testing was undertaken by a reliable operator on each

re

occasion. Injury history and anthropometric data were collated by qualified physiotherapists.

lP

For the purposes of this investigation, the dominant leg was considered the participant’s preferred leg when kicking a ball. Eccentric hamstring strength testing and motion analysis (for the break-point analysis) were captured simultaneously, with fascicle length measured

na

before any exercise on the same day. Chronic running loads greater than 80, and 90% of each player’s maximum velocity were collated from the preceding 28, and 56 days prior to each

Jo

ur

respective test.

The hamstring strength testing device (Vald Performance, Albion QLD

AUSTRALIA) and 3D motion capture (Vicon, Oxford UK) were set-up as per the manufacturer’s recommendations. Lower body plug-in gait was used for motion capture. Prior to testing, each participant was allowed a five-minute warm up consisting of one set of five double-leg repetitions as a warm-up. Testing consisted of one set of three single-leg

5

maximum eccentric contractions on each side, with the dominant leg tested first. During all efforts, the participants were advised to maintain a neutral/extended hip position. Average peak force (Newtons) across the three repetitions was recorded for each testing period. In addition, the corresponding knee angle of the tested limb at the time of reaching the below thigh angular velocities, was recorded for each maximal effort: 20deg/sec (corresponding to the start of the forward movement), 60deg/sec (corresponding to the period when the athlete began to ‘accelerate’ during the eccentric movement, and peak angular velocity which

ro of

represented loss of control of the movement. Additionally, the elapsed time period (milliseconds) between 20-60deg/sec and 20-peak velocity were recorded to account for the

time under load during the contraction. The results of the testing parameters are summarised

-p

in Table 1.

re

The processes used for the collection of BFlh architecture has been previously

lP

described22 . The extrapolation technique, whilst not a direct measure of fascicle length, has been successfully validated against cadaveric tissues and as such is considered a robust way of estimating fascicle lengths23. Muscle thickness, pennation angle and fascicle length of the

na

BFlh were determined utilising two-dimensional, B-mode ultrasound (frequency 12MHz; depth 8cm; field of view, 14 x 47mm) (GE Healthcare Vivid-I, Wauwatosa, WI). The site of

ur

assessment was determined as halfway between the ischial tuberosity and the popliteal

Jo

crease, along the line of the BFlh. All assessments were undertaken in a prone position with both the hip and knee extended, with the participant having undertaken 5mins of inactivity. The ultrasound probe, with a layer of conductive gel, was placed perpendicular to the posterior thigh on top of the measured scanning site. The orientation of the probe was then manipulated by a skilled assessor, with published reliability, until a clear image was obtained22. .

6

Once the images were collected, analysis was undertaken off-line (MicroDicom, Version 0.7.8, Bulgaria). For each image, fascicle length estimation was undertaken using the equation which was validated against cadaveric tissues23. The equation used was:

FL = sin(AA +90°) x MT/sin [180° - (AA+180° - PA)] where:

ro of

FL = fascicle length, AA = aponeurosis angle, MT = muscle thickness and PA = pennation angle.

The results of these tests are indicated in Table 1.

-p

Fascicle length was reported in absolute terms (cm) from a single image and fascicle.

re

These data were collected from training within the previous 28 and 56 day periods prior to each respective testing block. The peak speed (m.s-1) achieved between tests and average

lP

7-day running volume (m) greater than 80%, and 90% of peak speed was calculated for the

na

preceding 28, and 56 days. The results of these data are summarised in Table 1.

Statistical analysis was performed using multiple using R-Studio Statistical package

ur

(version 1.1.423). A power analysis was derived from Cohen24 and sample size was determined so that the study had 80% power to detect an effect size as large as 0.7SD units

Jo

on the dependent variables of interest in the study, with an alpha value of 0.05, two-tailed. This analysis determined that 32 participants were required for sufficient statistical power to be achieved. In Cohen's terms, the effect size that the study was set up to detect is mediumlarge.

7

Results Thirty-three athletes were included in the final analysis. The group included outside backs (n=16), edge (n=6) and middle players (n=11). Mean fascicle length results are presented in Table 1 [INSERT TABLE 1 NEAR HERE]. Results across the group indicated fascicle length results of 10.11cm at testing 1 (pre-season), 10.65cm at testing 2 (late-preseason), and 10.52cm at testing 3 (in-season). Furthermore, mean force and motion analysis data is presented in Table 1. Results here indicate a mean Nordic peak force output of 407.3N

ro of

/ 4.16N/kg (IQR = 321-471; 3.52-4.72), 623miliseconds (IQR = 555-723) from start of forward movement until peak thigh angular velocity during the eccentric contraction, and 37.7deg (IQR = 42-32) knee angle at the time of peak angular velocity.

-p

Chronic load during the study period are indicated in Table 1. Results here indicate a

re

mean maximum velocity of 8.74m.s-1 (IQR = 8.3-9.2) with mean chronic load above 80% of the measured maximum speed 76.8m (IQR = 33.3-107.8) and 58.9m (IQR = 31.1-79.5) for

lP

the preceding 28 and 56-day periods, respectively. Mean speed volumes above 90% of the measured maximum speed measured 14 m (IQR = 3.3-20.0) and 9.7m (IQR = 3.4-13.7) for

na

the preceding 28 and 56-day periods, respectively.

ur

To examine the fixed-effect determinants of fascicle length, a multiple linear regression analysis was performed. This involved a backward stepwise regression from the full model

Jo

(all variables included) to arrive at the final model. The analysis of variance in is presented in Supplementary Table 2. This indicates that the predictors used in the final analysis to be statistically useful contributors to the final model. The summary of coefficients for the final model is indicated in Supplementary Table 1. The adjusted R-squared value for the final model on the current data set was 50.6 (F-value 8.62 on 9 and 58 df, p-value = 4.56e-08), indicating that 50.6% of the explained variability in fascicle length within the dataset was due

8

to the variables included in the final model. The relative contribution of each variable to the final model is indicated in Figure 1 [INSERT FIGURE 1 NEAR HERE]. The most important contributor to fascicle length within the observed dataset was running volume (measured in meters) >80% of the athletes measured maximum velocity (30%). Peak Nordic force output (27%) and elapsed time under load at long lengths (17%) rounded out the three highest contributors to fascicle length changes. Peak speed (13%), previous injury (8%) and age (5%) were other statistically significant contributors to the observed variability in fascicle length

ro of

within this dataset. Running volumes above 90% and angle-specific thigh angular velocities (20deg/s, 60deg/s and angle of peak thigh angular velocity) were not statistically significant determinants of fascicle length within this data set.

-p

The model assumptions (residuals plots) are highlighted in Figure 2. The model

re

assumptions are that the residuals are independent and are normally distributed, centred around zero and have a constant variance ( ~ N(0,2)). The observations in the Residuals vs

lP

Fitted plot, Scale-Location Plot and Residuals vs Leverage Plots (Figure 2) [INSERT FIGURE 2 NEAR HERE] are centred around zero with relatively constant variance. In the

na

normal QQ plot (Figure 2) there is some slight variance from the straight line particularly at the tails, and two observations are outside 2 standardised residuals suggesting they are

ur

potential outliers. However, a Shapiro-Wilks test was not significant (W = 1, p = 0.7) and so we can ascertain there is no evidence against the hypothesis that the residuals are normally

Jo

distributed.

Discussion

This is the first study in professional team sport athletes to identify determinants of BFlh fascicle length. We demonstrated relative chronic running loads >80% of maximum velocity explained around 43% of the variability in fascicle length, whilst the often9

recommended threshold above 90% was not a statistically significant contributor. Our findings also demonstrated that peak eccentric hamstring force was associated with 27% of the variance in BFlh fascicle length. When combined with prolonged eccentric time under tension at long muscle lengths (17%) these two factors described around 44% of the explained variability in fascicle length. Collectively, these findings may help guide conditioning and prevention strategies for athletes in the future. If practitioners are unable to monitor fascicle length changes, managing chronic running loads >80% of maximum

ro of

velocity as well as eccentric strength training may help estimate around 90% of the controllable determinants in BFlh fascicle length in their athletes.

Chronic running volume over 80% of maximum velocity during the preceding 56-day

-p

period was the largest contributor to the explained variability in fascicle length (30%). When

re

also combined with an athletes measured maximum velocity within this period (13% of the observed variability), this affirms previous literature which has advocated maintenance of

lP

chronic high speed running loads in the prevention of hamstring strain injury25,26. However, although regular exposure above 90% of the measured maximum velocity is often

na

recommended within high performance environments for HSI prevention27, the results of this study suggest that if the aim is to improve fascicle length, that this target may not be

ur

necessary. Although future research is required in this area, this study suggests that regular exposure above 80% of an athletes maximum velocity might be sufficient for the

Jo

optimisation of fascicle length in professional athletes. In turn, this may have subsequent benefits for HSI risk management. Peak eccentric strength was the second most important contributor to the explained variability of fascicle length (27%). Previous research has affirmed the benefits of eccentric training in optimising fascicle length adaptation8-10,14. The current study also found that time

10

under load at longer lengths (17% of the explained variability in fascicle length), not the ‘break point’ angle of the exercise, were significant influences on fascicle length adaptation. Previous literature7,15,27,28 has explored the concept of the break angle as a measure of potential HSI risk. The results of the current study suggest that break angle at 20deg/sec, 60deg/sec or angle of peak thigh angular velocity had a minimal effect on BFlh fascicle length modifications. In turn, it. would appear that it is the combined ability to sustain an elapsed time under supramaximal load that has the most important influence on fascicle

ro of

length adaptations. This may represent a useful addition to strength training programming in HSI prevention.

Age (5%) and previous injury (8%) were the final contributors to the explained

-p

variability in fascicle length within the dataset. Having a previous HSI and increasing age

re

have been extensively reported to augment the likelihood of an injury occurring 4,5. Although the results of this study reaffirm the importance of these factors, it is somewhat reassuring the

lP

majority of the model is explained by factors which can be modified through various interventions, allowing practitioners the ability to address an athletes risk.

na

Limitations of this study include firstly, the fact that data was collected over a single professional season. Although statistically significant influences on fascicle length changes

ur

were observed, we were able to explain just over 50% of the total variability in fascicle

Jo

length within this dataset, meaning that there are other statistical influences on fascicle length changes which we did not account for in this study. Although we conducted an analysis in order to achieve sufficient power within the study, continued observation over multiple seasons will further strengthen the predictive capability of these models, and further research should seek to explore additional influences on fascicle length such as heavy isometrics and other hamstring strength exercises as well as targeted flexibility and mobility work which has

11

also been advocated in HSI injury prevention. Secondly, the measure of fascicle length is an estimation made from a validated equation. This is due to the small transducer field of view being unable to capture an entire BFlh fascicle. However, whilst the results are still an estimation, the methodology and equation employed has been validated against cadaveric samples and shows excellent agreement between dissection and estimation methods23. Ideally transducers with larger fields of view or panoramic functions would be used, however such equipment and techniques are not available in our laboratory.

ro of

Conclusions Significant determinants of hamstring fascicle length were observed over a single

professional rugby league season. Chronic running load >80% of maximum speed (28 days

-p

and 56 days combined) and overall maximum speed explained 43% of the observed

variability in fascicle length, whilst strength-related variables collectively contributed an

re

additional 44%. Non-modifiable risk factors (age and previous injury) collectively

lP

contributed the remaining 13%. Future research should examine absolute predictive thresholds for physical performance-based tests and re-injury risk reduction, as well as seek to include additional training modalities over and above the ones included in this study as

na

means of further optimizing the explained influences on hamstring fascicle length for

ur

hamstring injury prevention in professional athletes.

Jo

Conflicts of interest:

There are no conflicts to declare

Acknowledgments: The authors would like to thank Liam Richardson, Steve Dean, Andrew Rondinelli, Bree O’Halloran and Matt Hogan for their assistance with this project

12

13

ro of

-p

re

lP

na

ur

Jo

Jo

ur

na

lP

re

-p

ro of

References 1. Hickey J, Shield AJ, Williams MD, et al. The financial cost of hamstring strain injuries in the Australian Football League. Br J Sports Med 2014;48(8):837-41. 2. Eirale C, Farooq A, Smiley FA, et al. Epidemiology of football injuries in Asia: A prospective study in Qatar. J Sci Med Sport 2013;16(2):113-17. doi: 10.1016/j.jsams.2012.07.001 3. Verrall GM, Kalairajah Y Fau - Slavotinek JP, Slavotinek Jp Fau - Spriggins AJ, et al. Assessment of player performance following return to sport after hamstring muscle strain injury. J Sci Med Sport. 2006 May;9(1-2):87-90. 4. Hägglund M, Waldén M, Ekstrand J. Previous injury as a risk factor for injury in elite football: a prospective study over two consecutive seasons. Br J Sports Med 2006;40(9):767-72. 5. Arnason A, Sigurdsson S, Gudmundsson A, Holme I, Engebretsen L, Bahr R. Risk factors for injuries in football. Am J Sports Med. 2004;32(1 Suppl):5S-16S. 6. Timmins RG, Ruddy JD, Presland J, et al. Architectural Changes of the Biceps Femoris Long Head after Concentric or Eccentric Training. Med Sci Sports Exerc 2016;48(3):499-508. 7. Sconce E, Jones P, Turner E, et al. The Validity of the Nordic Hamstring Lower for a Field-Based Assessment of Eccentric Hamstring Strength. J Sport Rehabil. 2015;24(1):13-20. 8. Al Attar W, Soomro N, Sinclair P, et al. Effect of Injury Prevention Programs that Include the Nordic Hamstring Exercise on Hamstring Injury Rates in Soccer Players: A Systematic Review and Meta-Analysis. Sports Med 2017;47(5):907-16. 9. Bourne M, Pizzari T, Timmins R, et al. An Evidence-Based Framework for Strengthening Exercises to Prevent Hamstring Injury. Sports Med 2018;48(2):251-67. 10. Shield AJ, Bourne MN. Hamstring Injury Prevention Practices in Elite Sport: Evidence for Eccentric Strength vs. Lumbo-Pelvic Training. Sports Med 2018;48(3):513-24. 11. Opar D, Williams M, Timmins R, Hickey J, Duhig S, Shield A. Eccentric hamstring strength and hamstring injury risk in Australian footballers. Med Sci Sports Exerc. 2014;47(4):857-65. PubMed PMID: 100021876. 12. Bourne MN, Opar DA, Williams MD, et al. Eccentric Knee Flexor Strength and Risk of Hamstring Injuries in Rugby Union: A Prospective Study. Am J Sports Med 2015;43(11):2663-70. doi: 10.1177/0363546515599633 13. Timmins RG, Bourne MN, Shield AJ, et al. Short biceps femoris fascicles and eccentric knee flexor weakness increase the risk of hamstring injury in elite football (soccer): a prospective cohort study. Br J Sports Med 2016;50(24):1524-35. doi: 10.1136/bjsports-2015-095362 14. Presland JD, Timmins RG, Bourne MN, et al. The effect of Nordic hamstring exercise training volume on biceps femoris long head architectural adaptation. Scand J Med Sci Sports 2018;28(7):1775-83. 15. Lee JWY, Cai M-J, Yung PSH, et al. Reliability, Validity, and Sensitivity of a Novel Smartphone-Based Eccentric Hamstring Strength Test in Professional Football Players Int J Sports Physiol Perform 2018;13(5):620-24. 16. Duhig S, Williams M, Ferguson C, Opar D, Shield A. Effect of high-speed running on hamstring strain injury risk. Br J Sports Med. 2015;50(24):1536-40. PubMed PMID: 112824928

14

Jo

ur

na

lP

re

-p

ro of

17. Ruddy JD, Pollard CW, Timmins RG, et al. Running exposure is associated with the risk of hamstring strain injury in elite Australian footballers. Br J Sports Med 2016 doi: 10.1136/bjsports-2016-096777 18. Stares J, Dawson B, Peeling P, et al. Identifying high risk loading conditions for inseason injury in elite Australian football players. J Sci Med Sport 2018;21(1):4651. 19. Rosenberg M, Lester L, Peeling P, et al. Preseason Workload Volume And High-Risk Periods For Noncontact Injury Across Multiple Australian Football League Seasons. J Strength Cond Res. 2017;31(7):1821-29. 20. Ruddy J, Shield A, Maniar N, et al. Predicting hamstring strain injury incidence in elite Australian footballers. J Sci Med Sport 2017;20:10-11. 21. Varley MC, Fairweather Ih, Aughey RJ. Validity and reliability of GPS for measuring instantaneous velocity during acceleration, deceleration, and constant motion. J Sports Sci. 2012;30(2):121-7. 22. Timmins R, Shield A, Williams M, et al. Biceps femoris long head architecture: a reliability and retrospective injury study. Med Sci Sports Exerc 2015;47(5):90513. 23. Kellis E, Galanis N, Natsis K, et al. Validity of architectural properties of the hamstring muscles: correlation of ultrasound findings with cadaveric dissection. J Biomech 2009;42(15):2549-54. doi: 10.1016/j.jbiomech.2009.07.011 24. Cohen J. A power primer. Washington, DC, US: American Psychological Association 2003. 25. Carey DL, Ong K, Whiteley R, et al. Predictive Modelling of Training Loads and Injury in Australian Football. Int J Comput Sci Sport 2018;17(1):49-66. 26. Ruddy J, Timmins R, Pollard C, Opar D. Running exposure is associated with the risk of hamstring strain injury in elite Australian footballers. Br J Sports Med. 2017;52(14):919-28. PubMed PMID: 121355237. 27. Taberner M, Cohen DD. Physical preparation of the football player with an intramuscular hamstring tendon tear: clinical perspective with video demonstrations. Br J Sports Med 2018;52(19):1275. 28. Timmins R, Shield A, Williams M, et al. Is There Evidence to Support the Use of the Angle of Peak Torque as a Marker of Hamstring Injury and Re-Injury Risk? Sports Med 2016;46(1):7-13.

15

ro of

ur

na

lP

re

-p

Figure 1: Contributors to biceps femoris fascicle length from the linear regression analysis

Jo

Figure 2: Residuals plots for the final model predicting biceps femoris long head fascicle length in elite Rugby League athletes.

16

Table 1: Fascicle length, eccentric hamstring strength, Nordic performance measures as well as and GPS speed and distance measures in elite Rugby League athletes. Fasci Eccentric Elapsed Knee Angle At GPS Measures cle

Hamstri

Time

Specific Thigh

Lengt

ng

During The

Angular Velocity

h

Measure

Nordic

(Deg)

s

(Millisecon ds)

Pea

N/

20-

20-

ge

k

kg

60d

Peak

(cm)

For

B

eg

Veloc

ce

W

20de g/s

118.

m

.7

4

3

9.91c

321

3.5

288.

Qtr.

m

.5

2

3

Medi

10.44

387

3.9

365.

cm

.1

3

0

10.34

407

4.1

ur

369.

cm

.3

6

1

10.74

471

4.7

430.

Qtr.

cm

.2

2

0

Max

11.48

743

7.3

681.

cm

.7

6

7

an Mea

Jo

n 3rd

554.6

636.7

na

1st

156.7

623.3

Max

93.35 82.28

84.93 71.66

78.96 65.75

76.17 61.30

25.53 20.37

>90

%

%

ity

ed

(28

(56

(28

(56

(deg/s

(m/s

day)

day)

day) day)

0.00

3.439

0.00

)

-1)

64.20

6.98 1

41.88

8.33 8

36.71

8.77 7

80.43 67.26

>90

%

37.70

8.74

32.00

9.24 8

936.7

>80

%

3 723.3

>80

Spe

-p

2.3

re

203

lP

8.99c

Peak

g/s Veloc

ity

(N) Min

60de

ro of

Avera

12.67

10.1 95

0.00

0 33.2

31.05

3.26

3.41

9

5

3

4

60.5

45.72

10.4

6.43

4

0

53

4

76.8

58.91

13.9

9.70

2

8

57

1

107.

79.46

19.9

13.6

82

3

74

85

327.

231.8

58.5

41.0

00

66

65

06

Measured in metres

17

Jo

ur

na

lP

re

-p

ro of

cm = centimetres, n = newtons of force, N/kg BW = newtons of force relative to body weight, deg/s = degrees per second, deg = degrees, GPS = Global Positioning System, m/s-1 = metres per second squared

18